Multi-Objective Deployment of UAVs for Multi-Hop FANET: UAV-Assisted Emergency Vehicular Network

Author:

Li Haoran1ORCID,Hao Xiaoyao2,Wen Juan1,Liu Fangyuan34,Zhang Yiling2

Affiliation:

1. State Key Laboratory of Integrated Service Networks, Xidian University, Xi’an 710071, China

2. Hangzhou Institute of Technology, Xidian University, Hangzhou 330100, China

3. School of Information Engineering, Xi’an University, Xi’an 710065, China

4. School of Information Engineering, Xi’an Fanyi University, Xi’an 710105, China

Abstract

In the event of a sudden natural disaster, the damaged communication infrastructure cannot provide a necessary network service for vehicles. Unfortunately, this is the critical moment when the occupants of trapped vehicles need to urgently use the vehicular network’s emergency service. How to efficiently connect the trapped vehicle to the base station is the challenge facing the emergency vehicular network. To address this challenge, this study proposes a UAV-assisted multi-objective and multi-hop ad hoc network (UMMVN) that can be used as an emergency vehicular network. Firstly, it presents an integrated design of a search system to find a trapped vehicle, the communication relay, and the networking, which significantly decreases the UAV’s networking time cost. Secondly, it presents a multi-objective search for a trapped vehicle and navigates UAVs along multiple paths to different objectives. Thirdly, it presents an optimal branching node strategy that allows the adequate use of the overlapping paths to multiple targets, which decreases the networking cost within the limited communication and searching range. The numerical experiments illustrate that the UMMVN performs better than other state-of-the-art networking methods.

Funder

National Natural Science Foundation of Chin

Foundation of Shaanxi Province

Publisher

MDPI AG

Reference20 articles.

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3. Thuy, N.D.T., Bui, D.N., Phung, M.D., and Duy, H.P. (2022, January 21–24). Deployment of UAVs for Optimal Multihop Ad-hoc Networks Using Particle Swarm Optimization and Behavior-based Control. Proceedings of the 2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS), Hanoi, Vietnam.

4. Lee, H., Zhu, Y., Wapenski, D., Wang, X., Zhang, Q., Palacharla, P., and Ikeuchi, T. (2019, January 18–21). A Stochastic Process based Routing Algorithm for Wireless Ad Hoc Networks. Proceedings of the 2019 International Conference on Computing, Networking and Communications (ICNC), Honolulu, HI, USA.

5. Covert Communications in Air-ground Integrated Urban Sensing Networks Enhanced by Federated Learning;Wang;IEEE Sens. J.,2023

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